Revolut made £120K in revenue in 2015. Last year it made £4.5B.

It started as a prepaid card for people tired of losing money on exchange rates abroad. Today it has 68 million retail customers and £1.7B in pre-tax profit.

• 2015: launched with a free card and the interbank rate

• 2017: Premium, Business and crypto all launched in the same year

• 2021: first full-year profit

• 2023: £1.8B ($2.2B) in revenue and £438M in pre-tax profit

How did it get there? Every year Revolut gave the same customers a new reason to use the app:

• Foreign exchange brought them in

• Current accounts made them open it every day

• Subscriptions, trading and crypto added revenue on top

• Local IBANs, deposits and credit turned a travel card into their main bank account

We went through eight years of Revolut's accounts and annual reports. Each chapter below takes one milestone on that curve, from £1M to $2B, and breaks down the products and growth moves that got Revolut there.

Refer a friend

Inside you will find:

1. Path to £1M: Win the First 300,000 Customers With One Cheaper Exchange Rate See how a free card and the interbank rate pulled in 300,000 users while every one of them lost money.

2. Path to £10M: Launch Every Paid Product in a Single Year Find out how Premium, Business, euro IBANs and crypto all shipped in 2017, and how crypto access became a referral reward.

3. Path to £50M: The Free-Card Referral That Tripled Daily Signups Learn why giving a friend a free card beat cash rewards, and how Metal built a 60,000-person waitlist.

4. Path to £100M: Add Stock Trading and Go From 3.5M to 10M Customers See how trading, Apple Pay and new countries tripled customers while partnerships became a managed channel.

5. Path to £200M: How Revolut Grew 45% When Travel Stopped Find out how a travel card kept growing through the pandemic with no marketing spend.

6. Path to £500M: How Crypto Made Revolut Profitable See how FX and Wealth reached 55% of revenue in the first profitable year, and what the auditors flagged.

7. Path to £1B: How Revolut Replaced the Crypto Revenue It Lost Learn how cards, subscriptions and interest filled the gap when FX and Wealth revenue fell by £79M.

8. Path to $2B: How Interest Income Grew From £83M to £500M See how deposits, credit and local accounts turned Revolut into its customers’ main bank.

9. The Revolut Playbook in 5 Moves Take the five moves and apply them to your own roadmap and distribution.

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   An Inside Breakdown of How Cognition Found Its First Customers, Bought Windsurf in a Weekend and Reached $1B in 24 Months

2. The Bending Spoons Playbook: From $40K to an $18B IPO
   How a Failed Startup From Milan Learned to Buy Product-Market Fit and Win Every Deal It Bids On

3. How Glean Grew From $100M to $300M ARR in 15 Months
   The $60K-to-$5M Land-and-Expand Loop and the “Cut Your AI Bill” Pitch That Beat Microsoft

4. The $100M GTM Playbook
   How the Fastest-Growing AI Startups Built Their Sales and Marketing Machines

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Before AI, getting from $1M to $100M in under two years was a record. Today ten startups have done it, six of them in a year or less.

So we took the 10 startups that reached $100M ARR the fastest (AI labs excluded) and broke down how they sold. For each one, we looked at:

• How many people they had in sales and marketing

• Which GTM motions brought in the revenue

• Which tools their teams run on

• What they did at each stage, from the first customer to $100M

The pattern? Creators and the product do the selling for much longer than they used to. Then every one of these companies builds a sales team anyway.

Refer a friend

Inside you will find:

1. How Top AI Startups Reached $100M ARR

   1. Higgsfield Find out how a 150-person creative team and paid creators got it to $100M with no paid ads.

   2. Lovable See how 45 people reached $100M through the product, the community and launch after launch.

   3. Manus Learn how an invite-only launch and a 2 million waitlist turned into $100M in eight months.

   4. Emergent See how 100+ creators a week sold an app builder to people who can’t code.

   5. Replit Find out how four sales reps handled a company that grew from $2.8M to $150M in a year.

   6. Cursor See how a code editor grew 10% a week on product alone, then built an enterprise sales org.

   7. Legora Learn how lawyers selling to lawyers, plus a Jude Law campaign, built the fastest direct-sales company.

   8. ElevenLabs See how voice actors, an API and a 20x quota turned inbound into $100M.

   9. Sierra Find out how paid design partners and outcome-based pricing got Sierra into the Fortune 1000.

   10. Clay See how Clay runs its own GTM, with 60% self-serve revenue and zero cold outbound.

2. AI Startups’ GTM Tools See which tools show up across the GTM job posts of these companies.

3. The Playbook Stage by Stage Learn what to build between $0 and $1M, $1M and $10M, and $10M and $100M.

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Railway started 2026 at around $20M in ARR. It is now about to cross $100M.

It has 40 employees and one founder.

• A $100M Series B in January, led by TQ Ventures

• More than 2 million developers on the platform

• $90M of its own data center hardware

• No sales team until last year

Railway is a cloud where developers, and now their coding agents, deploy apps and databases without touching servers. Many developer platforms sit on top of AWS or Google Cloud and pay their prices. Railway runs on servers it bought, so its margin grows with usage.

Its founder? Jake Cooper left Uber in 2020 and set up a box of databases for his side projects. He posted it on Twitter asking who he should talk to about a job. He got zero job offers and a few angel checks.

Inside you will find:

1. Why Two Co-Founders Is the Worst Number Find out why Jake never looked for a co-founder and how he gets outvoted on purpose.

2. How Railway Survived Losing $500K a Month See why he killed the free tier and brought it back only once Railway owned its hardware.

3. Solve the Problem Before You Look at How Stripe Did It Learn the innovation tokens rule for deciding what to reinvent and what to buy.

4. Say No to 90% of Ideas With One Question: Why Now? Copy the one-page abstract every Railway initiative needs before it reaches planning.

5. Do the Job Manually Before You Hire for It Build the role spec from work you’ve already done, and see how Railway keeps its people.

6. The Six-Week Onboarding: Trust, Clarity, Judgment Copy the plan that took a new hire to owning the entire edge network within a year.

7. Write Values That Check Each Other See how Railway’s four values work as brakes on each other, and what one of them cost.

8. Move One Brick a Week, 52 Times a Year Set up the weekly rhythm and the 36 offline hours behind Jake’s biggest decisions.

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It took seven months and a team of under 200 people.

For most people, it’s the first time an AI does the work for them.

The person behind it? Alexandr Wang, co-founder of Scale AI and Meta’s Chief AI Officer since 2025. This week he explained how Muse was built:

• A first prototype ready in two weeks

• A spreadsheet of 100+ behaviours that decided the launch date

• Memes from his own X account as the main marketing

• More than 200 researchers reporting directly to him

Inside you will find:

1. Build Where Your Company Has an Unfair Advantage Learn why Meta stayed out of the coding race and bet on personal AI.

2. Ship a Prototype in Two Weeks, Then Spend Seven Months Making It Work See how the first Muse demo reached the board in days and what the rest of the year was for.

3. Decide What “Ready to Launch” Means Before You Build The 100-row spreadsheet that decided when Muse shipped, and how to build yours.

4. Why Great Products Need One Point of View How Muse stayed under 200 people and kept every PM from adding their own feature.

5. Your Ads Should Show What the Product Does for the Customer Why the big AI labs’ campaigns missed, and the screenshot test every consumer product must pass.

6. How the Founder’s Memes Drove Muse’s Growth The posting strategy behind “make Meta cool again” and why the internet rewards risk.

7. Get Users to a Wow Moment, Then Make Every Task a Little Bigger Find out how the “trust fall” turns first-time users into daily users.

8. When the Company Is Broken, Rebuild It From Scratch What Meta did after Llama 4, and the small flat team Wang built in its place.

9. Do Every Job at Your First Company, Then Become the Coach How Wang went from running every decision at Scale to managing 200+ direct reports at Meta.

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Most founders who try to copy this flood their account with hundreds of creators and thousands of near-identical talking-head videos, then watch Meta cluster and suppress the reach to zero.

We went through Hector Serrano's full breakdown of the program he built as WisprFlow's content lead (that went super viral on x) , pulled the exact numbers, and cross-checked the Tribe performance model and WisprFlow's current pricing against first-party sources.

What came back is not a tool review. It is a copyable 30-day rebuild of a paid ads engine that runs on culture, not spend.

In this guide you'll find:

1. Why performance-based UGC kills the old creative risk model

2. The payment model: pay 7% of ad spend, not per video

3. The smart retainer: how to recruit top creators before you have any track record

4. Start with 4 to 5 creators, not hundreds, or Meta will suppress you

5. Where to actually find your first creators: the Instagram keyword search method

6. Treat creators like a coached sales team, not a content vending machine

7. The scaling cadence: 5 to 50 in four months by doubling, then coasting at 40 to 60

8. How to scale hiring without lowering the bar: referrals and exclusivity

9. The one thing that separates leaderboard creators: relentless experimentation

10. What to steal: your 30-day rebuild checklist

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1. Why performance-based UGC kills the old creative risk model

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As every ambiotius founder, I’ve been fascinated by the story of Adam Neumann and WeWork since I first knew about it (I even interviewed the current WeWork CEO, a legend btw).

A company valued at $47 billion filed an S-1 showing $3 billion in losses over three years, roughly $219,000 lost for every hour it operated, and then collapsed in weeks.

After that, I’ve followed Adam’s new business, Flow and was waiting to see what he’d do next. Call me naive, but I believe he’s out there trying to build one of the greatest companies in the world.

So when he published this interview, I knew I had to dissect it.

So I went and found the most valuable insights fron the interview, and broke them to you.

In this guide you’ll find (sorry if it’s too long)

1. The 95% claim against $3 billion in losses: how Neumann frames his own collapse

2. The money wound: why a brutal childhood became the engine that built and nearly broke him

3. The hole a number never fills: why chasing valuation is a founder’s trap

4. The $300,000 arbitrage that became WeWork: Green Desk’s exact unit economics

5. Dream to the stars, execute the basics: the two-places-at-once operating rule to become a legendary founder

6. How to know who are your real friends

7. First principles on a $90,000 budget: the flooring quote cut from $45,000 to $12,000

8. One building to two a day: when the company outgrows the founder

9. Power comes from influence, not control: the leadership rule Neumann learned too late

10. The unit economics almost nobody reports: WeWork was profitable the moment it stopped growing

11. A $300M ask became a $3B offer signed in under 30 minutes: the Masa deal that changed everything

12. WeWork’s core financial mistake: long leases against short commitments

13. The walk downtown where ego replaced mission: the real beginning of the end

14. Benioff’s rejected advice: IPO at a discount instead of taking SoftBank

15. Build from your truth, not the customer’s wish list: the Henry Ford rule

16. Choose investors by their worst-day behavior: the 6-year filter

17. The $20 billion buyout the board turned down chasing $32 billion

18. Forced public before he was ready: the S-1 that said $219,000 lost per hour

19. If you stab the king, kill him: the super-voting-share playbook that took him out

20. The $460 million personal guarantee and the partner who answered on the worst day

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Mark Cuban started his first company with $500 from his first customer.

He had just been fired from a software store in Dallas and was sleeping on the floor of a three-bedroom apartment he shared with five friends. He told the customer that if the software didn’t work, he would wash their car.

What came after:

• MicroSolutions, sold to CompuServe in 1990

• Broadcast.com, sold to Yahoo for $5.7B in 1999, with Cuban still owning a third

• The Dallas Mavericks, bought for $285M in 2000

• Cost Plus Drugs, launched in 2022 with 111 medications

What would he build today? We asked him in Las Vegas last October. His answer was AI, repeated six times.

Since then he has given founders the same playbook in every interview: learn agents, walk into small businesses and charge for the work they never get to.

Inside you will find:

1. Get Paid by Customers Before You Raise From Investors See why Cuban treats cash as more important than revenue and raising money as an obligation.

2. Know Your Business Better Than Anyone Trying to Kill It The learning habit he built reading software manuals at night, and still runs today with agents.

3. Bet on the Ideas People Call Stupid Learn how to tell a contrarian bet from a bad idea, and why you only have to be right once.

4. Sell Trust and Let Your Customers Do the Marketing The trust formula behind Cost Plus Drugs, and the cookie company making $12M in profit with zero ads.

5. Hire People Who Cover Your Weaknesses His startup rules on teams, the day his partner told him he was a jerk, and why star hires rarely save a company.

6. Use AI to Show Up With the Work Already Done Build the 12-minute business plan and the weekly price report, and pass the test he now runs on every founder.

7. Start Where Small Businesses Need AI Most The $100-an-hour agent business he would start at 20, and the Rebel Cheese agent that recovers $50K a month.

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1. Get Paid by Customers Before You Raise From Investors

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This year, Alphabet, Amazon, Meta, Microsoft and Oracle will spend about $780 billion building AI capacity.

Only 2% of S&P 500 companies track what AI does for them over time.

The rest of a16z’s new State of Markets report points the same way:

• 69% of the S&P 500 already runs AI in production

• the top 1% of AI users spends about 8x more than the top 10%

• 86% of US venture dollars went to AI companies this year

• startups that raised recently still grow as fast as they did in 2021

What it means for you? Companies are spending on AI faster than they can prove what it returns. The startups that close that gap for their customers are the ones winning budgets and rounds right now, and the data shows exactly where they sit.

Inside you will find:

1. How to Sell AI Your Buyers Can Measure See why 69% of large companies run AI but only 2% track it, and build that metric into your product.

2. Why Your First Customers Should Be Power Users Find out how the top 1% of AI users pulls away from everyone else, and how to find them in your market.

3. How to Cut Your Inference Bill While Compute Gets More Expensive Learn the caching, routing and fine-tuning moves that keep margins healthy as GPU prices rise.

4. Which Software Still Gets Paid, and the Path Your Company Should Take See why cyber and vertical software held up, and how to choose between growth and margins.

5. The Numbers You Need to Raise in 2027 Compare your growth, margin and runway with the benchmarks investors are using today.

6. Where a16z Is Looking to Invest Next Find out the seven areas a16z is focusing on, with the startups already winning in each.

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1. How to Sell AI Your Buyers Can Measure

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Bill Gates and Paul Allen sold Microsoft’s first product before they had written it.

The founders behind the biggest companies of the last 50 years all got their first customers with moves that look small, a bit awkward and impossible to scale:

• Steve Jobs called Bill Hewlett at 12 and asked him for parts

• Brian Chesky flew to New York to photograph his hosts’ homes himself

• Facebook took 60% of Harvard in 10 days before going anywhere else

• Patrick Collison walked out of a cinema to fix one user’s error

• Jensen Huang told Nvidia’s first big customer that his chip didn’t work, and still left with $5 million

The problem? Because none of this scales, most founders skip it. And these are the moves that bring in the first 100 customers.

Inside you will find:

1. Why Steve Jobs Says Most Founders Never Get a Yes
   See how a phone call at 12 got Jobs his first job at HP, and why most founders never make that call.

2. How Airbnb Got Its First 100 Hosts to Love It
   Find out why Chesky and Gebbia flew to New York to meet every host, and what they did once they got there.

3. How Microsoft Sold Its First Product Before Writing It
   Learn how Gates and Allen closed MITS with a letter, an all-nighter and a demo that worked on the second try.

4. Why Facebook and PayPal Started With Tiny Markets
   See how winning 60% of Harvard and 30% of eBay power sellers set up two of the biggest companies ever built.

5. How Stripe Turned Its First Users Into Evangelists
   Find out why every user error at early Stripe rang the whole team’s phones, even at the cinema.

6. How Nvidia Kept Sega After Failing Them
   Learn how Jensen Huang told his only big customer the chip didn’t work and still left with $5M.

7. How to Make Selling a Daily Habit
   See why Kalanick and Neumann think fear and comfort stop most founders, and how to keep knocking on doors.

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1. Why Steve Jobs Says Most Founders Never Get a Yes

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Bending Spoons started in 2013 with about $40.000, the money left over from a failed startup.

On July 1, 2026, it listed on Nasdaq at $29 a share, a valuation of about $18.4 billion. Since then:

• it closed the acquisition of Airtable, at an enterprise value of $1.285 billion

• it agreed to buy Miro, at $1.355 billion

• it reported $704 million of revenue in a single quarter, up 126% in a year

What they do? Bending Spoons buys software products that already have millions of users, rebuilds them with its own engineers and tools, and keeps them forever. Evernote, AOL, Vimeo, WeTransfer, Eventbrite and Airtable all belong to it, and it has never sold a significant business it bought.

Most startups spend years looking for product-market fit, the moment a product finds a market that really wants it. Bending Spoons buys products that already have it, and makes money by running them better than their previous owners could.

Inside you’ll find:

1. How Bending Spoons Decided to Buy Product-Market Fit Why a failed AI startup and $40,000 convinced three engineers to stop betting on luck.

2. How a $10K App Grew Into a $4B Revenue Machine The first acquisition, the debt ladder, and the Grindr deal that almost took over the company.

3. How They Win Every Deal They Bid On The pricing model and why the highest price always wins.

4. What Happens the Day After They Buy a Company Evernote from 350 people to 20, AI agents fixing bugs, and how they handle layoffs.

5. The Team Behind Bending Spoons The founders and the rules they run on: no titles, no bonuses, every job up for grabs.

6. Why Nobody Has Copied Bending Spoons Why private equity structurally can’t, and the numbers that show the gap.

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1. How Bending Spoons Decided to Buy Product-Market Fit

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New business creation on Stripe is up almost 2x in a year.

That jump is bigger than the one Stripe saw during the COVID lockdowns. And since Stripe now handles a bit more than a quarter of all new Delaware incorporations, it is close to a picture of the whole market.

The new companies are also doing better:

• Average revenue per new company went up slightly, even with twice as many of them

• 20% of Stripe Atlas startups charged their first customer within 30 days in 2025, up from 8% in 2020

• The time to reach $1M, $10M and $100M in recurring revenue has roughly halved

The question? What to build!

Patrick Collison answered it in a conversation with Replit’s founder. He would start trying things right away, go after industries still running on clunky 1990s software and look at what is popular among young people but still low status.

Inside you will find:

1. Why This Is the Best Time in History to Start a Company See the Stripe data behind the surge and why Collison’s first rule is to try anything.

2. How to Find the 1990s Software Still Running Your Industry Let Claude audit the incumbent software in any vertical and score where it fails.

3. How to Spot Markets That Are Popular but Low Status Find the behavior young people pay for that incumbents still ignore.

4. Why the AI Labs Won’t Eat Your Startup Learn where value goes when intelligence gets cheap, and test your idea against the labs.

5. How to Build a Moat With Hamilton Helmer’s 7 Powers Check which of the seven powers your idea can reach, and at what stage.

6. Why the Long Tail Is the Safest Place to Build Size a niche big enough to pay you and too small to attract big competitors.

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📈 Startup Playbooks
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1. Why This Is the Best Time in History to Start a Company

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On September 25, Cognition crossed $1 billion in annualized revenue.

Twenty-four months earlier, it was at $1 million.

In March 2024 its launch video went viral, and within weeks developers were taking it apart online. The company had no customers and no revenue. Since then:

• it raised three rounds in twelve months, the last one at $48 billion

• it bought Windsurf, a company five times its size, in 72 hours

• its own agent now writes about 90% of its code

What they do? Cognition builds Devin, an AI software engineer.

Most AI coding tools sit inside the editor and suggest the next lines while a developer types. Devin works on its own: you assign it a ticket in Slack or Jira, it opens its own machine, writes the code, tests it and comes back with a pull request for a human to approve.

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Inside you’ll find:

1. How a Debunked Demo Found Its First Paying Customers Why the first pilots failed, which boring task gave them product-market fit, and why they cut the price from $500 to $20.

2. How to Buy a Company Five Times Your Size in One Weekend The 72 hours between Google hiring Windsurf’s founders and Cognition signing the deal on Monday.

3. How Devin Came to Write 90% of Cognition’s Code How a team of a few dozen engineers went from 13% to 90% of code written by its own agent in five months.

4. How Forward Deployed Engineers Sell Devin to Goldman and the US Navy The enterprise motion that compresses an 18-month vendor cycle into three months.

5. The Team Behind Cognition An olympiad cohort of former founders, and the hiring tactics that brought them in.

6. The Road to $1B ARR What the revenue curve, three rounds in a year and a tiny burn say about the climb.

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1. How a Debunked Demo Found Its First Paying Customers

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We went through interviews, essays, founder letters and old clips from some of the most influential entrepreneurs in tech to understand what they actually do differently.

Here are 7 principles from Peter Thiel, Elon Musk, Sam Altman, Marc Andreessen, Mark Zuckerberg and Travis Kalanick that any founder can apply:

1. Build around something you believe that others don’t

2. Put disproportionate time into what can kill the company

3. Ask users what they hate, not what they like

4. Believe in yourself before anyone else has a reason to

5. Commit to a thesis before it becomes obvious

6. Move fast while thinking in decades

7. Learn how to keep going when the market says no

We traced each principle back to their own words!

Inside you will find:

1. The One Question That Tells You If Your Startup Idea Is Worth Building

   Peter Thiel’s contrarian test, and why a consensus idea gets competed down to zero margin.

2. How Musk Turned Speed Into More Shots Before the Money Ran Out

   The allocation rule hiding behind the famous 22-hour days.

3. The Feedback Question That Makes Users Tell You the Truth

   The exact line Musk uses with friends, and why praise teaches you nothing.

4. Why Your Self-Belief Is What Gets Your First Hires and Investors to Bet

   Sam Altman’s rule on self-belief “almost to the point of delusion,” and the check he puts on it.

5. How to Commit to a Thesis Years Before It Looks Obvious

   What Marc Andreessen’s 2011 “software is eating the world” bet teaches about holding a position.

6. How Zuckerberg Runs Fast Shipping and Ten-Year Bets at the Same Time

   The two clocks written into Facebook’s IPO letter.

7. How to Outlast the Market’s No, and the Line Kalanick Says He Crossed

   Four years without a salary at Red Swoosh, and his own account of running “too close to the line.”

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1. The One Question That Tells You If Your Startup Idea Is Worth Building

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RonanRx went from $0 to $541K in eight weeks.

All of it word of mouth.

• Five people

• 50% growth week over week

• a pharmacy licensed in 33 states that did not exist ten weeks earlier

What they do? Drug companies work by manufacturing millions of identical units and pushing them out through wholesalers, pharmacies and insurers, each taking a cut on the way through. That is why any drug reaches you in a fixed doses at the price it does.

→ RonanRx makes one vial at a time, and it owns every step of the way there. A doctor sets a dose for your body, RonanRx manufactures that exact vial in its own pharmacy, and it arrives at your door in two days. The consultation, the prescription, the factory and the delivery all sit inside one company!

Inside you will find:

1. David vs Goliath: Why They Can Beat Big Pharma

2. Growing to Half a Million With Software-Like Margins

3. How It Works: From Manufacturing to Your Front Door

4. The Slack-Like Growth Loop

5. The Road to $1B ARR

6. The Team Behind RonanRx

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To give you a taste, here are a few more pitch deck breakdowns from some of the most promising companies coming out of Y Combinator:

1️⃣ ⁠Lightsprint (YC P26) → Everyone Can Ship Code and That’s Exactly the Problem

2️⃣ ⁠Gojiberry (YC P26) → How Scaled to $3.5M ARR in 11 Months

3️⃣ Arga Labs (YC P26) → How Hit $40K MRR in 7 Weeks

4️⃣ Thomas (YC P26) → The First AI Founder YC Ever Backed

5️⃣ Trellis (YC P26) → How grew to $614K ARR in 6 weeks

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1. David vs Goliath: Why They Can Beat Big Pharma

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In a recent talk (and essay), Paul Graham revealed the two numbers that determine how big a startup can get:

• how fast it grows

• how long that growth can continue

To show what they mean, he started with a company making $10,000 a month. At 15% monthly growth, it would be making roughly $44 million a month five years later. The calculation takes seconds. The difficult question is whether a startup can keep growing long enough for the math to matter.

That depends on more than a promising chart:

• Are users coming back and telling their friends?

• Is there enough demand beyond your first group of customers?

• And which of those two numbers is actually holding your company back?

Inside you will find:

1. The Math Behind a Billion-Dollar Startup

   See how two numbers can turn $10,000 in monthly revenue into $44 million.

2. The Growth Rate YC Actually Measures

   Find out what to track each week and how your growth compares with YC’s benchmarks.

3. Why Word of Mouth Is the Growth That Compounds

   Measure whether users love your product enough to bring in the next ones.

4. Why Paul Graham Tells Founders to Stop Worrying About Market Size

   Learn why a small, urgent market can be the starting point for a much bigger company.

5. Why the Best Startup Ideas Sound Bad at First

   Spot the needs and overlooked problems that could become your strongest ideas.

6. What Changes When Anyone Can Build in a Weekend

   See why finding out what users want now matters more than shipping a first version.

7. The Billion-Dollar Kit: Run It on Your Startup Today

   Six tools to test your growth, word of mouth and market, then decide what to fix first.

Granola’s revenue motion runs on Attio. Here’s what that adds up to:

• Zero missed leads and 10X faster access to customer context

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1. The Math Behind a Billion-Dollar Startup

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On the morning of YC Demo Day in September 2023, Pablo Palafox, his brother Javier, and Luis Paarup decided to kill their company.

They had entered the batch with $70,000 in annual recurring revenue. They left with a computer vision product they no longer believed in and a plan to fire every customer.

Thirty-five months later, HappyRobot raised $150 million at a $1.2 billion valuation. Its AI agents now work with DHL, leading US freight brokers, and more than 150 enterprise customers.

We’ve also had a front-row seat to part of that journey: we invested in HappyRobot and sat down with the founders after their Series B. This story draws on that conversation, along with other interviews and podcasts.

Inside you’ll find:

1. How HappyRobot Found a Market Worth Building For
   Why they left paying customers behind to build for the companies that move goods by truck.

2. What Made Voice the Hardest Problem to Solve
   Why their first customers wanted an AI agent that could answer calls and negotiate the price of a delivery.

3. How One Live Demo Became a Seven-Figure Account
   How a Discord demo opened the door to their first major customer.

4. From a $30K Deal to a $1.2B Valuation
   How engineers working with customers turned deployments into larger accounts.

5. The Team Behind HappyRobot
   Three founders with different strengths built the company around clear roles, close customer work and ambitious hiring.

6. What the Numbers Actually Say About HappyRobot’s Growth
   What its funding, customers, and contracts reveal about the climb.

This issue is available exclusively to paid subscribers!

Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ +40 AI Pitch Decks (Ultimate Collection) — the best-funded AI startups of 2026, slide by slide.

💰 Investor Database & Tools
↳ The Ultimate Fundraising Guide to Raise Millions — The Most Complete Fundraising Package: 6,600+ investors across family offices, angels, VCs and corporate funds.

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1. How HappyRobot Found a Market Worth Building For

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Garry Tan, Jared Friedman, Diana Hu and Harj Taggar went through the batch-level data on every company accepted in the last eighteen months: which sectors grew, by how much, which ones are producing revenue in weeks and what kind of founder is winning inside each one.

• A fifth of the batch has moved into atoms

• A quarter is building agents that do an entire job on their own

• A layer of suppliers almost nobody talks about is selling training data to the frontier labs at eight and nine figures

• And the founders outperforming everyone are solo operators in their forties and fifties

Below is the full build list: the categories, the number YC disclosed for each one, and what each one asks of you if you decide to go after it.

In this guide you’ll find:

1. Start With Atoms

   Hard Tech Went From 8% to 20% of the Batch

2. Why You Can Afford to Build Hardware Now

   Codegen Removed the Thousand-Engineer Requirement

3. Sell to the Buyers Nobody Is Serving

   Defense Contracts and Detroit Manufacturing

4. Build the Picks and Shovels of Compute

   Sites, Power, Silicon and the Switch Bottleneck

5. Get Into Robotics Before the ChatGPT Moment

   The Benchmark Jumped From 10% to 70%

6. Own the Footage Your Robot Learns From

   Why Every YC Robotics Company Fine-Tunes

7. Build the Place Where the Work Happens

   Why Salesforce Grew While Everyone Called SaaS Dead

8. Build Agents That Do the Whole Job

   The Path From Zero to Seven Figures in Three Months

9. Sell to the Labs

   Data and RL Environments Are a Nine-Figure Category

10. Go Solo If You Have Been Around the Block

    Solo Founders Tripled to 19%

This issue is available exclusively to paid subscribers!

Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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Pocket FM added $250M in net new ARR last year to cross $500M, and it did so while EBITDA-profitable, a claim almost no AI-content company can make.

Here’s the through-line before you read a word of tactics: Pocket didn’t win by making content cheaper with AI.

It won by finding the one metric whose tiny movement cascades through the whole business, then rebuilding the company around manufacturing that number. Steal that discipline, not the category.

In this guide you’ll find:

1. How Pocket FM Cut CAC 30% While Increasing Ad Spend 8x

2. The 3-Year Experiment That Turned 25 Minutes of Usage Into 2.5+ Hours

3. The International Growth Playbook That Increased Retention 50%

4. How a $1M Bet Became a $15M ARR Business in 60 Days

5. The Decision That Stalled a $200M ARR Company, Then Added $250M in One Year

6. 5 Growth Systems From Pocket FM You Can Copy This Quarter

This issue is available exclusively to paid subscribers!

Paid subscribers unlock the full library: 200+ decks, 10,000+ investors, AI Agent playbooks, and fresh high-signal content every week.

Here’s a good place to start:

🤖 AI Agent Templates
↳ The McKinsey Slide Playbook for Claude — how to build consulting-grade presentations in minutes.

📈 Startup Playbooks
↳ The AI Founders Playbook — lessons from Sequoia, OpenAI, Nvidia, and LangChain on building AI startups from zero.

🎯 The Deck Library
↳ 27 Most Promising AI Startup Pitch Decks Backed by Top Investors — the best-funded AI startups of 2025, slide by slide.

💰 Investor Database & Tools
↳ The Family Office List — 1,000 family offices actively writing cheques. Used by 5,000+ founders raising their round.

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We’re already 80,000+ founders and operators inside!

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